• Assert statement: A construct in many programming languages is used to check if a condition is true and raise an exception if it is not.
• AssertionError: An error caused by a failed assertion in a program.
• Assertions: A way of checking that the assumptions made by the program are true, and raising an exception if they are not. Assertions are usually used during the development process to catch logical errors and to check the internal consistency of the program.
• AttributeError: An error caused by trying to access an attribute or method that does not exist on an object.
• Breakpoints: A feature of many debuggers that allows the developer to pause the execution of a program at a specific line of code, allowing them to inspect the state of the program and variables at that point.
• Bullet Point List All Errors: Terminology and Related Definitions.
• Call Stack: A data structure that keeps track of the sequence of function calls that have been made in a program, allowing the developer to see the flow of control in the program and the state of variables at each point.
• Chaos Engineering: The practice of intentionally introducing controlled failures or errors into a system to test its resilience and fault-tolerance. This helps organizations identify and address potential issues before they cause real problems.
• Circuit Breaker: A pattern used in software development to prevent a failing service from being overwhelmed by requests, by automatically “tripping” a circuit and temporarily stopping requests to the service, until the service is back to normal.
• Code Reviews: A process of reviewing the code written by other developers in order to identify errors, suggest improvements and ensure the code quality.
• Continuous Integration: A software development practice in which code is integrated and tested frequently, often multiple times a day, in order to identify and fix errors as soon as they are introduced.
• Debugging: The process of finding and fixing errors in a program.
• Defensive programming: A programming paradigm that emphasizes the prevention of errors by proactively checking for and handling them, rather than relying on the program to gracefully handle unexpected inputs or conditions.
• Distributed Tracing: A technique used to trace the flow of a request or a transaction across multiple systems in a distributed system. It allows to understand the end-to-end flow of a request, including how it is handled by each system and how long it takes to complete.
• EOFError: An error caused by trying to read past the end of a file.
• Error Alerting: The process of setting up alerts to notify developers or operations teams when an error occurs, so that they can take action to fix the error.
• Error Analytics: The process of analyzing error data to understand the cause of errors, how often they occur, and how they impact the performance and usability of
• Error Boundaries: A concept in React.js and other component-based frameworks, where a component can “catch” an error thrown by its children and display a fallback UI, rather than crashing the entire application.
• Error Budget Alarm Fatigue: A phenomenon where operators and users become desensitized to the constant alerts and notifications generated by a system, resulting in a decreased ability to respond to and resolve errors.
• Error Budget Alarm: A notification system that alerts the development or operations team when the error budget drift exceeds the acceptable limits, so that they can take action to reduce errors.
• Error Budget Anomaly Detection: The process of identifying unusual or abnormal patterns in the error rate, MTBF, and MTTR, which may indicate potential issues or problems.
• Error Budget Auditing: The process of reviewing and evaluating the error budget and related processes, procedures, and metrics to ensure compliance and effectiveness.
• Error Budget Automation: The use of software tools and scripts to automate the tracking, monitoring, and management of the error budget.
• Error Budget Benchmarking: The process of comparing the error budget of a system to industry standards or best practices in order to identify areas for improvement.
• Error Budget Burn Rate: The rate at which an organization’s error budget is being used up. It helps to determine whether the organization is on track to meet its error budget or if additional steps need to be taken to reduce errors.
• Error Budget Canary: A technique of deploying new features or changes to a small subset of users before releasing them to everyone, in order to test for errors and gather feedback.
• Error Budget Capacity Management: The process of planning, allocating, and managing the resources of a system to ensure that it can meet the error budget targets and service level agreements.
• Error Budget Capacity Planning: The process of forecasting and planning for the future capacity needs of a system, including the ability to handle errors and failures.
• Error Budget Circuit breaker: A software design pattern that can be implemented to prevent a system from being overwhelmed by errors, by temporarily disabling certain functionality or requests when a certain threshold of errors is reached.
• Error Budget Compliance Checking: The process of checking and verifying that the error budget and related processes and procedures are in compliance with organizational policies and regulations.
• Error Budget Compliance Testing: The process of testing a system to ensure that it meets the error budget targets and service level agreements outlined in the compliance policy.
• Error Budget Compliance: The level of adherence to the error budget policy, guidelines, and regulations set by the organization.
• Error Budget Continuous Improvement: The process of continuously monitoring and improving the error budget, including the identification and implementation of best practices and new technologies.
• Error Budget Continuous Integration and Deployment (CI/CD): The process of automating the build, testing, and deployment of software, including the monitoring and management of the error budget.
• Error Budget Correlation: The process of identifying a correlation between different types of errors, to understand if multiple errors are caused by a common source.
• Error Budget Cost of Quality (COQ): The total cost associated with quality control and error management, including the cost of errors, the cost of preventing errors, and the cost of detecting and correcting errors.
• Error Budget Drift: The difference between the actual error rate and the error budget. It helps to determine whether the organization is on track to meet its error budget or if additional steps need to be taken to reduce errors.
• Error Budget Allocation: The process of determining how much of the total error budget should be allocated to different components, services, or teams within a system.
• Error Budget Audit: The process of conducting an independent review of the error budget, including the assessment of policies, procedures, and controls, and the identification of opportunities for improvement.
• Error Budget Automation: The use of technology and automation tools to monitor, track, and manage the error budget, including the generation of alerts and notifications, the collection and analysis of data, and the implementation of mitigation strategies.
• Error Budget Backup and Disaster Recovery: The process of creating and maintaining backups of data and systems, and developing plans for restoring data and systems in the event of an incident or error.
• Error Budget Benchmarking: The process of comparing the performance and error rate of a system to industry standards and best practices, in order to identify opportunities for improvement and to measure progress over time.
• Error Budget Budgeting: The process of allocating a certain amount of budget to cover the error budget, including the costs of monitoring, incident response, and mitigation.
• Error Budget Business Continuity Planning: The process of developing and implementing plans and procedures to ensure that essential business functions can continue in the event of an error or incident, including the identification of critical systems and processes, the development of backup and recovery strategies, and the testing of continuity plans.
• Error Budget Capacity Planning: The process of predicting and planning for future resource usage, including the estimation of the system’s maximum capacity, the identification of bottlenecks, and the implementation of strategies to ensure that the system can handle anticipated loads.
• Error Budget Change Management: The process of managing changes to a system, including the identification of potential impacts, the assessment of risk, the development of a change plan, and the communication of changes to stakeholders.
• Error Budget Communication Plan: The process of developing and implementing a plan for communicating with stakeholders during an incident or error, including the identification of key stakeholders, the use of different communication channels, and the development of standard messaging and templates.
• Error Budget Communication: The process of communicating and reporting on the error budget, including the sharing of data and information with stakeholders and the development of metrics and dashboards to facilitate understanding and decision making.
• Error Budget Compliance Management: The process of ensuring that a system is compliant with relevant regulations and standards, including the identification of applicable regulations and standards, the assessment of compliance, and the development and implementation of compliance plans.
• Error Budget Compliance Monitoring: The process of monitoring the system to ensure compliance with regulatory requirements and industry standards, including security, privacy, and data protection regulations.
• Error Budget Compliance: The process of ensuring that a system or organization is adhering to the error budget policies, procedures, and guidelines established.
• Error Budget Configuration Management: The process of identifying, organizing, and controlling the configuration of a system, including the identification of components, the tracking of versions, and the management of dependencies.
• Error Budget Contingency Planning: The process of planning for unexpected errors or incidents, including the identification of potential risks, the development of mitigation strategies, and the allocation of resources.
• Error Budget Continual Improvement: The process of continuously monitoring, analyzing, and improving the error budget, including the identification of trends and patterns, the implementation of new strategies and technologies, and the alignment of the error budget with the overall goals and objectives of the organization.
• Error Budget Dashboard: A visual representation of error budget data and information, including metrics, alerts, and notifications, designed to provide a comprehensive view of the system’s performance and error rate.
• Error Budget Allocation: The process of allocating a portion of the error budget to different parts of the system, based on the potential impact of errors in those parts, the likelihood of errors occurring, and the cost of preventing or recovering from those errors.
• Error Budget Automation: The use of technology, such as software tools, to automate the process of monitoring and tracking the error budget, and to make adjustments to the error budget, as needed.
• Error Budget Communication: The process of communicating the error budget and the errors that have occurred, to the stakeholders and affected parties, to keep them informed of the status of the system and the error budget, and to involve them in the decision-making process.
• Error Budget Dashboard: A visual representation of the error budget and the errors that have occurred, that provides real-time information about the usage of the error budget, and allows for easy monitoring and tracking of the error budget.
• Error Budget Governance: The process of setting, enforcing and monitoring policies, procedures and standards that govern the use of the error budget, to ensure that it is used effectively and efficiently.
• Error Budget Optimization: The process of analyzing the error budget and the errors that have occurred, to identify areas where the error budget can be used more effectively and efficiently, and to make adjustments to the error budget, as needed.
• Error Budget Review: The process of reviewing the error budget and the errors that have occurred, to identify trends and patterns, and to make adjustments to the error budget, as needed.
• Error Budget Tracking: The process of monitoring and tracking the usage of the error budget, including the number of errors that occur, the cost of preventing or recovering from those errors, and the remaining error budget available.
• Error Budget: A predetermined amount of errors that an organization is willing to tolerate in a system, within a specific timeframe. This is used to set priorities for incident response and recovery efforts and to manage the trade-offs between the cost of preventing errors and the cost of dealing with errors that occur.
• Error Budget Error Handling: The process of dealing with errors that occur in a system, including the detection, isolation, and recovery from errors, as well as the implementation of countermeasures to prevent errors from happening again in the future.
• Error Budget Error Prevention: The process of identifying potential errors and implementing countermeasures to prevent them from occurring in the first place. This includes the use of best practices, the development of error-proofing procedures, and the use of tools and technologies to help detect and prevent errors.
• Error Budget Error Reduction: The process of identifying and resolving errors that occur in a system, in order to improve the overall reliability and performance of the system. This includes identifying the causes of errors, implementing countermeasures to prevent them from happening again, and monitoring the system to ensure that the errors do not recur.
• Error Budget Error Tolerance: The ability of a system to continue to operate or perform a specific function in the event of an error or failure. This includes the ability of a system to detect errors, isolate them, and recover from them without a significant impact on performance or availability.
• Error Budget Escalation Management: The process of identifying and managing situations that require increased attention or resources, including the identification of trigger points or thresholds, the development of escalation procedures, and the assignment of roles and responsibilities.
• Error Budget Forecasting: The process of predicting and forecasting the likelihood and impact of errors, based on historical data and trends, in order to proactively manage and mitigate potential issues.
• Error Budget Forecasting: The process of predicting future errors or incidents based on historical data, current trends, and other relevant factors, in order to anticipate and prepare for potential issues.
• Error Budget Governance Committee: A group of individuals responsible for overseeing the error budget governance framework, including the development and implementation of policies, procedures, and standards.
• Error Budget Governance Framework: A set of policies, procedures, and standards for the management and control of errors and failures in a system, including the roles and responsibilities of personnel, the management of risks, and the measurement of performance.
• Error Budget Impact Analysis: The process of assessing the potential impact of an error or incident on the system, its users, and the organization as a whole. This includes identifying the scope of the impact, the likelihood of the impact occurring, and the potential consequences of the impact.
• Error Budget Incident Management: The process of identifying, analyzing, and resolving incidents or errors that occur in a system, including the identification of root causes, the implementation of countermeasures, and the tracking and reporting of progress.
• Error Budget Incident Management: The process of managing incidents and errors as they occur, including the identification and resolution of underlying issues, the communication of status updates to stakeholders, and the implementation of recovery and mitigation strategies.
• Error Budget Mitigation: The process of reducing the impact and severity of errors or incidents, including the implementation of countermeasures, the use of fallback mechanisms, and the execution of recovery plans.
• Error Budget Monitoring and Alerting: The process of monitoring the performance, availability, and security of a system, and the use of alerts to notify stakeholders of potential or actual errors or incidents.
• Error Budget Optimization: The process of identifying and implementing opportunities for improvement and optimization within the error budget.
• Error Budget Performance Management: The process of monitoring, analyzing, and optimizing the performance of a system, including the identification of bottlenecks, the measurement of key performance indicators (KPIs), and the implementation of performance-enhancing strategies.
• Error Budget Planning: The process of forecasting and planning for the error budget, including the identification of potential risks and the development of strategies to mitigate them.
• Error Budget Post-Incident Review: The process of reviewing an incident or error after it has occurred, in order to identify lessons learned, areas for improvement, and best practices for future incidents.
• Error Budget Prioritization: The process of determining the priority of errors or incidents based on their impact, severity, and likelihood, and allocating resources and attention accordingly.
• Error Budget Problem Management: The process of identifying, analyzing, and resolving problems that are causing or contributing to errors or incidents in a system. This includes the identification of root causes, the implementation of countermeasures, and the tracking and reporting of progress.
• Error Budget Recovery Point Objective (RPO): The maximum amount of data loss that an organization can tolerate after an incident or error.
• Error Budget Recovery Point Objective (RPO): The maximum amount of data that can be lost as a result of an incident or error, before it begins to cause significant harm to the organization. This is used to set priorities for incident response and recovery efforts.
• Error Budget Recovery Time Objective (RTO): The maximum amount of time that a system can be down before it begins to cause significant harm to the organization. This is used to set priorities for incident response and recovery efforts.
• Error Budget Recovery Time Objective (RTO): The maximum amount of time that an organization can tolerate for a system or process to be unavailable after an incident or error.
• Error Budget Recovery: The process of restoring a system to normal operation after an error or incident, including the identification and resolution of underlying issues, and the communication of status updates to stakeholders.
• Error Budget Reporting: The process of collecting, analyzing, and reporting on error budget data, including metrics such as error rate, MTBF, and MTTR, as well as other relevant information such as incident reports, root cause analysis, and post-incident reviews.
• Error Budget Retention: The process of retaining historical data on errors and incidents, including the collection of metrics, logs, and other relevant information, and the use of this data to improve the management and performance of the system.
• Error Budget Review: The process of regularly reviewing and evaluating the error budget, including the identification of trends, patterns, and opportunities for improvement.
• Error Budget Risk Management: The process of identifying, analyzing, and addressing risks that could impact the availability, performance, and security of a system, including the development of mitigation strategies, the tracking of progress, and the reporting of results.
• Error Budget Rollback: The process of undoing a system change or update that caused an error or incident, in order to restore normal operation.
• Error Budget Rollout: The process of introducing error budgeting to a system or organization, including the development of policies, procedures, and guidelines, as well as the training of personnel.
• Error Budget Root Cause Analysis (RCA): The process of identifying the underlying cause of an incident or error, in order to prevent it from happening again in the future. This includes identifying the factors that led to the incident, and analyzing the process, system or human behavior that contributed to it.
• Error Budget Root Cause Analysis: The process of identifying the underlying cause of an error or incident, including the identification of contributing factors, and the implementation of countermeasures to prevent future occurrences.
• Error Budget Security Management: The process of identifying, analyzing, and addressing security risks that could impact the availability, performance, and security of a system, including the development of security plans, the use of security best practices, and the management of security-related incidents and errors.
• Error Budget Service Level Agreement (SLA): A formal agreement between an organization and its customers or clients that outlines the level of service and availability that will be provided, and the conditions under which service credits or other compensation may be provided in the event of errors or incidents.
• Error Budget Service Management: The process of managing the delivery of services to customers or clients, including the development of service level agreements (SLAs), the measurement of service level performance, and the management of service-related incidents and errors.
• Error Budget Simulation: The process of simulating different scenarios and conditions in order to test the system’s ability to handle errors and failures, and to identify opportunities for improvement.
• Error Budget Testing: The process of testing the system and its components in order to identify and address potential errors or vulnerabilities. This includes functional testing, performance testing, load testing, stress testing, and security testing.
• Error Budget Tracking: The process of monitoring and tracking the error budget, including the collection and analysis of data on error rate, MTBF, and MTTR.
• Error Budget Vendor Management: The process of managing the relationships and performance of third-party vendors or service providers, including the identification of vendors, the assessment of vendor performance, and the management of vendor-related incidents and errors.
• Error Budget Escalation: The process of escalating errors or incidents that exceed the error budget targets, including the notification of higher-level personnel and the implementation of additional measures to resolve the issue.
• Error Budget Escalation: The process of escalating errors to higher-level teams or authorities when they exceed the acceptable limits.
• Error Budget Escalation: The process of taking additional steps to reduce errors when the error budget drift exceeds the acceptable limits.
• Error Budget Fallback: A strategy of providing an alternative or fallback functionality when an error occurs, in order to reduce the impact of the error on the user and the system.
• Error Budget Forecasting: The process of predicting the error rate, MTBF and MTTR of a system based on historical data and trending analysis.
• Error Budget Governance: The process of establishing and maintaining policies, procedures, and standards for the management and control of errors and failures in a system.
• Error Budget Impact Analysis: The process of evaluating the potential impact of an error or failure on the system and its users, including the financial and operational consequences.
• Error Budget Incident Classification: The process of categorizing incidents and errors based on their severity, impact, and cause.
• Error Budget Incident Management: The process of managing and responding to incidents and errors, including the identification, investigation, and resolution of issues.
• Error Budget Incident Response: The process of responding to an incident or error, including the identification, investigation, and resolution of issues, and the implementation of appropriate measures to prevent recurrence.
• Error Budget Management Dashboard: A tool that allows teams to monitor the error budget drift, track the MTBF, MTTR, and other error-related metrics, and view the error budget allocation and consumption over time.
• Error Budget Management Framework: A set of guidelines, tools, and best practices for managing and optimizing the error budget.
• Error Budget Metrics: The set of measurements and metrics used to track and monitor the error budget, such as error rate, MTBF, and MTTR.
• Error Budget Modeling: The process of creating mathematical or simulation models to represent the behavior of a system and its errors.
• Error Budget Optimization: The process of identifying opportunities to improve the error budget by reducing the error rate, increasing the MTBF, and decreasing the MTTR.
• Error Budget Performance Tuning: The process of optimizing the performance of a system by identifying and addressing bottlenecks, inefficiencies, and other issues that may contribute to errors and failures.
• Error Budget Performance: The measure of how well a system is able to handle errors, in terms of the impact on performance, availability, and usability.
• Error Budget Policy: A set of rules and guidelines that dictate how an organization’s error budget should be used and managed. It might include rules around when and how to roll back a new release, for example, or when to perform an incident post-mortem.
• Error Budget Post-Incident Review (PIR): The process of conducting a review of an incident or error after it has been resolved, including the identification of lessons learned and opportunities for improvement.
• Error Budget Post-Mortem Analysis: A review of an incident or error that occurred, including the root cause, impact, and actions taken to prevent it from happening again in the future.
• Error Budget Prioritization: The process of determining the priority of errors based on the impact they have on the system and the users.
• Error Budget Quotas: A system that limits the number of errors that can occur in a given period of time, or that limits the number of users who are affected by errors.
• Error Budget Recovery Plan: A plan outlining the steps to be taken in case of an error or failure, including procedures for incident management, root cause analysis, and post-mortem analysis, and how to recover from it.
• Error Budget Remediation: The process of implementing changes or solutions to address the root cause of an error and prevent it from happening again in the future.
• Error Budget Reserve: A buffer or safety margin built into an error budget to account for unexpected errors or fluctuations in error rate.
• Error Budget Resilience: The ability of a system to withstand errors and failures, recover from them quickly, and continue to function in a degraded state.
• Error Budget Retry: A strategy of retrying a failed request or operation, in order to reduce the number of errors that occur.
• Error Budget Risk Management: The process of identifying, assessing, and mitigating the risks associated with errors and failures in a system, including the implementation of contingency plans and fallback strategies.
• Error Budget Rollback: The process of reversing a change or rolling back to a previous version of a system when the error budget drift exceeds the acceptable limits.
• Error Budget Rollout: The process of introducing changes or new features to a system while staying within the error budget. This can include things like gradually rolling out changes to a small percentage of users before releasing them to everyone, or monitoring the error rate closely and rolling back changes if necessary.
• Error Budget Root Cause Analysis (RCA): The process of identifying the underlying cause of an error or incident, including the collection and analysis of data, and the identification of contributing factors.
• Error Budget Root Cause Analysis: The process of identifying the underlying cause of an error, including identifying contributing factors and potential solutions.
• Error Budget Root Cause Identification: The process of identifying the underlying cause of an error by analyzing data, logs, and other information related to the incident.
• Error Budget Root Cause Mitigation: The process of implementing changes or solutions to address the root cause of an error, in order to prevent it from happening again in the future.
• Error Budget Runbook: A guide that outlines the steps to be taken in case of errors or failures, including procedures for incident management, root cause analysis, and post-mortem analysis.
• Error Budget Self-Healing: A technique of automatically detecting and resolving errors in a system, without the need for human intervention.
• Error Budget Service Level Agreement (SLA): A formal agreement between the development team and the business or customer outlining the expected level of service and availability for a system or service, including error budget targets and metrics.
• Error Budget Service Level Indicator (SLI): A metric used to measure the service level of a system or service, such as error rate, MTBF, or MTTR.
• Error Budget Service Level Objective (SLO): A specific, measurable, and time-bound goal for the availability and performance of a service or system, that is aligned with the overall service level agreement and error budget targets.
• Error Budget Testing: A technique of testing a system for errors by simulating different failure scenarios, in order to identify and address potential issues before they cause real problems.
• Error Budget Throttling: A technique of slowing down or limiting the rate of requests to a system in order to reduce the number of errors that occur.
• Error Budget Time To Detect (TTD): The time it takes to detect an error or incident after it has occurred.
• Error Budget Time To Recover (TTR): The time it takes to recover from an error or incident after it has been detected.
• Error Budget Trend Analysis: The process of analyzing the trends in the error rate, MTBF, and MTTR over time in order to identify patterns and make predictions about future behavior.
• Error Budget: A concept in DevOps and SRE (Site Reliability Engineering) where an organization sets a budget for the number of errors or failures that are acceptable in a system, and uses that budget to inform decisions about how to prioritize and address errors and failures.
• Error Budgets: A concept in which an organization sets a budget for the number of errors or failures that are acceptable in a system, and uses that budget to inform decisions about how to prioritize and address errors and failures.
• Error Codes and HTTP status codes: A standard way of indicating the outcome of an HTTP request, such as success, failure, or a specific error condition.
• Error Codes: A numeric or symbolic value that is returned or raised to indicate that an error has occurred.
• Error Handling Best Practices: Error handling is an important aspect of software development and there are several best practices that should be followed in order to make sure that errors are handled correctly and the system is robust. Some of these include: 1) Use exceptions rather than error codes for signaling errors. 2) Avoid returning error codes from constructors. 3) Catch exceptions as close to the point of origin as possible. 4) Always check the return value of new.
• Error Logging: A technique of storing the error information, such as error messages, stack traces, and environment information, in a log file or a database, to be used for later analysis and debugging.
• Error message design: The practice of designing clear, helpful error messages that inform the user of what went wrong, and how to fix it.
• Error Messages: A human-readable string that describes an error that has occurred.
• Error Monitoring: The process of monitoring an application for errors and collecting data about those errors in order to understand the cause of the errors and how to fix them.
• Error Rate: The number of errors that occur in a system, usually measured as a percentage of total requests or transactions.
• Error Tolerance: The ability of a system to continue functioning even when errors occur. This can be achieved by implementing techniques such as redundancy, failover, and load balancing, as well as by designing the system to be able to handle and recover from errors.
• Exception Handling in Distributed Systems: Exception handling in distributed systems can be more complex than in a single system because errors can occur at multiple points in the system, and it can be difficult to determine the cause of an error or to coordinate the handling of an error across multiple systems.
• Exception Handling: The process of dealing with exceptions and errors in a program, including catching, handling, and recovering from them.
• Exception Hierarchy: A way of organizing exceptions into a hierarchy, based on their relationship to one another. This allows exceptions to be caught and handled based on their type, rather than having to catch and handle every exception individually.
• Exception Hierarchy: The organization of exceptions into a tree-like structure, with more specific exceptions inheriting from more general ones.
• Exception Logging: A technique of storing the information about an exception, such as the exception message, stack trace, and environment information, in a log file or a database, to be used for later analysis and debugging.
• Exception Propagation: The process of an exception being passed up the call stack, through the sequence of function calls that led to the error, until it is handled or the program crashes.
• Exception Propagation: The process of passing an exception up the call stack, from the point where it was thrown to the point where it can be handled. This allows errors to be handled at the appropriate level of the program, rather than having to handle them locally in every function that might throw an exception.
• Exception Safety Guarantees: A term used to describe the level of protection provided by a function or class in the event of an exception. Some functions or classes provide strong exception safety guarantees, such as the guarantee that the program state will remain unchanged if an exception is thrown. Others provide weaker guarantees, such as the guarantee that the program state will be restored to a consistent state.
• Exception Safety in Inheritance: Exception safety in inheritance can be difficult to achieve because a derived class may throw exceptions that are not handled by the base class. To ensure exception safety in inheritance, it is important to document the exceptions that may be thrown by a class and its derived classes, and to handle exceptions appropriately.
• Exception Safety in Polymorphism: Exception safety in polymorphism can be difficult to achieve because a derived class may override a virtual function in a way that throws an exception that is not handled by the base class. To ensure exception safety in polymorphism, it is important to document the exceptions that may be thrown by a class and its derived classes, and to handle exceptions appropriately.
• Exception Safety in Templates: Exception safety in templates can be difficult to achieve because the template parameter types may not be known at compile time. To ensure exception safety in templates, it is important to document the exceptions that may be thrown by a template, and to handle exceptions appropriately.
• Exception Safety Levels: There are three levels of exception safety guarantees: 1) No-throw guarantee – a function that is guaranteed not to throw any exception. 2) Basic guarantee – a function that guarantees that the program will not crash, but does not guarantee that the program state will be unchanged. 3) Strong guarantee – a function that guarantees that the program state will be unchanged if an exception is thrown.
• Exception Safety: A term used to describe the degree to which a program is able to handle and recover from exceptions without losing data or corrupting memory.
• Exception Translation: The process of converting one type of exception into another, in order to provide a more appropriate or meaningful exception to the caller. This can be useful when an exception thrown by a library or third-party code does not provide enough information to be useful, or when the exception is not appropriate for the caller to handle.
• Exception: A general term for an error or exceptional condition that occurs during the execution of a program.
• Fallback logic: A technique used in software development to provide an alternative action or solution when a primary action or service fails. This helps to improve the availability and robustness of the system.
• Fault Tolerance: The ability of a system to continue functioning even when hardware or software components fail. This can be achieved by implementing techniques such as redundancy, failover, and load balancing, as well as by designing the system to be able to handle and recover from failures.
• FileNotFoundError: An error caused by trying to open a file that does not exist.
• Fuzzing: A technique used to test the robustness of a program by providing it with a large number of unexpected or malformed inputs in order to identify inputs that cause the program to crash or behave unexpectedly.
• GameDay: A technique of simulating various failure scenarios by introducing chaos in a controlled environment to test a system’s ability to handle those failures.
• GDB: A popular command line debugger for C, C++, and other programming languages, that can be used to inspect the state of a program while it’s running and find errors.
• Global Exception Handler: A function or class that is responsible for catching and handling all unhandled exceptions in an application. It can be used to provide a consistent way of handling errors across an entire application, rather than having to handle errors in each individual component or function.
• Handled Exception: An exception that has been caught and handled by the code using a try-except block, and does not cause the program to crash.
• ImportError: An error caused by a failure to import a module or package.
• Incident Management: The process of managing and responding to errors and failures in a system.
• IndentationError: An error caused by incorrect indentation in a Python program.
• IndexError: An error caused by trying to access an element of a container (e.g. list, tuple) using an index that is out of range.
• Integration Testing: A technique used to test how different parts of a program interact with each other, by combining them and testing them as a whole.
• IOError: An error caused by an input/output operation, such as reading from a closed file.
• KeyError: An error caused by trying to access a key in a dictionary that does not exist.
• Logic Error: An error in the design of a program that causes it to produce incorrect or unexpected results, but does not prevent it from running.
• Mean Time Between Failures (MTBF): The average amount of time that elapses between failures in a system.
• Mean Time To Recovery (MTTR): The average amount of time it takes to recover from a failure in a system.
• Memory Dump: A feature of some debuggers that allows the developer to examine the contents of memory at a specific point in the execution of a program, in order to understand how the program is interacting with memory and identify errors or issues.
• MemoryError: An error caused by a lack of memory when trying to allocate memory for a new object or data structure.
• NameError: An error caused by a variable or function not being defined or not in scope when it is referenced.
• OverflowError: An error caused by a numeric operation resulting in a value outside the range of the data type.
• Post-Mortem Analysis: The process of reviewing an incident after it has been resolved, in order to understand what caused it, how it was handled, and what can be done to prevent similar incidents in the future.
• Post-Mortem: A retrospective analysis of an incident or error, often conducted after the incident has been resolved, in order to understand what went wrong, how it could have been prevented, and what steps can be taken to prevent it from happening again.
• Profiling: The process of measuring the performance of a program and identifying bottlenecks or areas that are causing poor performance.
• raise statement: A construct in many programming languages used to raise an exception or error manually.
• RecursionError: An error caused by a function calling itself too many times, resulting in a stack overflow.
• Regression Testing: A technique used to test that a program continues to work correctly after changes have been made to it, by re-running previously passed test cases.
• Retry Logic: A technique used in software development to automatically retry a failed operation a certain number of times before giving up. It helps to handle temporary failures and improve the overall reliability of the system.
• Root Cause Analysis: The process of identifying the underlying cause of a problem or error, rather than just the symptoms. This can involve analyzing data, interviewing stakeholders, and looking for patterns in the data.
• Root Cause Analysis: The process of identifying the underlying cause of an error or failure, rather than just addressing the symptoms. This helps organizations understand why an error occurred and how to prevent it from happening again in the future.
• Runtime Error: An error that occurs during the execution of a program, such as a division by zero or trying to access an array out of bounds.
• Semantic Error: An error in the meaning of a statement or expression in a program, such as using a variable that has not been initialized.
• Stack trace analysis: A technique of analyzing the stack trace information to identify the sequence of function calls that led to an error and the state of the program at the time of the error, in order to understand the cause of the error and how to fix it.
• Stack Trace: A report of the sequence of function calls that led to an error, including the line of code where the error occurred and the values of any variables at the time of the error.
• Stepping: A feature of many debuggers that allows the developer to step through the execution of a program line by line, watching how the program’s state changes as it runs.
• Stress Testing: A technique used to test the limits of a program by providing it with a large amount of data or traffic in order to identify performance bottlenecks or other issues.
• Syntax Error: An error in the structure of a statement or expression in a programming language, often causing the program to fail to execute.
• SystemError: An error caused by an operating system or other low-level system problem.
• TabError: An error caused by mixing tabs and spaces for indentation in a Python program.
• Traceback: A report of the complete call stack of an error, including the line of code where the error occurred and the sequence of function calls that led to the error.
• try-except block: A construct in many programming languages used to handle exceptions and errors that may occur in a program.
• TypeError: An error caused by using the wrong type of value for a variable or function, such as using a string instead of an integer.
• UnderflowError: An error caused by a numeric operation resulting in a value smaller than the minimum representable value of the data type.
• Unhandled Exception: An exception that is not caught and handled by the code, causing the program to crash.
• Unit Testing: A technique used to test individual components or functions of a program in isolation from the rest of the program to ensure that each part works correctly.
• Use RAII (Resource Acquisition Is Initialization) Exception specification: A way of indicating which exceptions a function may throw. It is used to indicate that a function may throw an exception and to specify which types of exceptions it may throw.
• Valgrind: A popular tool for memory debugging and profiling of C and C++ programs that can detect memory leaks, buffer overflows, and other errors.
• ValueError: An error caused by passing an invalid value to a function or method.
• Watchpoints: A feature of some debuggers that allows the developer to pause the execution of a program when a specific variable or memory address is accessed or modified.
• ZeroDivisionError: An error caused by trying to divide a number by zero.

In summary, error budget management is a proactive approach to managing and mitigating errors that occur in a system. It involves various activities such as impact analysis, recovery time and point objectives, error budget allocation, tracking and review, governance, optimization, dashboard, automation, and communication. The goal is to balance the cost of preventing errors with the cost of dealing with errors that occur and to ensure that the system can operate within the allocated error budget without causing significant harm to the organization. This includes identifying the error, assessing the impact, and taking appropriate action to resolve the issue and prevent it from happening again.